Creating a feedback loop is the basis for all business administration. Digital video business is no different from any other venture. Of course the most common unit for measuring is money. Sales figures and advertising revenue are the basis for evaluating product’s commercial success. This is all common knowledge, but there is really no need to restrict the measuring to just monetary units or to the use of businesses.
The goal of all businesses should be to maximize the value they create to their customers. In a fully networked business environment no real advantage can be gained from holding back information. Data can most often be acquired or gathered from another source. Thus sharing the knowledge with the customer will become the most attractive strategy. Changing the mindset from a marketing and business intelligence driven company to a demand-controlled venture will require a significant cognitive leap. We will explain why it will however become absolute necessity.
The most significant part of the digital media company’s value creation has been the creation or identification of commercially viable content. How to find out what interests the public? A process for measuring and making adjustments to marketing and delivery activities based on the initial results has been the key enabler. However if this information becomes public company’s price negotiation position would be very weak for failures. Content has mostly been judged only on their artistic merits by the public.
The public as a community can benefit greatly from using measurement techniques to their own advantage. Theoretically information of media consumption can now be gathered and aggregated by peers in real time. No services offer this kind statistical information yet to the consumers, but data is already trickling further down the chain. Consequently in the future there is only space for companies that create content that is very well adapted to demand. The price/quality-ratio has to be right or the public can just choose something else from vast abundance of digital content available.
As the long tail of content makes it possible for the audience to be global from consumer point of view the direct monetary feedback opportunity to producer diminishes in importance. There are always alternatives available. Knowing what kind of stuff is needed more stays the producers headache. It is in consumers’ best interests to allow choose favourite producers and let them know what the consumer as the audience is interested in. Gathering data about video consumption could be integrated into the chosen aggregator’s portal backend. This is potentially huge change that will affect not only what will be produced, but also the rapidity of the product development cycle.
If we look at measuring in a bit more theoretical level it is evident that any control stimulus capture can be considered as measurements. There is a wide array of different things to measure: audience age, subjective picture quality, physical body reactions etc. There is also different alternatives to measuring. Choosing between quantitative and qualitative, data or free-form feedback are all possible options. As measuring should not impede consumption in any way effortlessness is the most important factor. Using automated measuring processes and information technology to analyze data is thus required.
What makes measurements exciting is really not the data, but how it can be used. Information can first of all be used to directly administer any of the tasks described in the previous posts. The home entertainment system could control capture, processing and consuming of fully personalized media content. If some more signal processing and storing capability is added the services can actually be taught and learn to match each individual user’s consumption habits. Further more matching these habit profiles customer groups can be found that may or more likely may not correspond with traditionally accepted business intelligence segments.
The conventional wisdom in the entertainment industry has relied on human experience and solid figures. Tomorrow it is more and more important to know what each customer is likely to like in the future. Automating measurements as projected in this post can help predictions a lot, but humans are for now needed for modelling the business environment and human behaviour.